The present invention relates generally to systems and methods for controlling a gas turbine engine. More specifically, the present invention relates to adaptive model-based control systems and methods that maximize capability after deterioration, fault, failure or damage to one or more engine components or systems so that engine performance and/or operability can be optimized.
Mechanical and electrical parts and/or systems can deteriorate, fail or be damaged. Any component in a gas turbine system, including engine components, sensors, actuators, or any of the engine subsystems, is susceptible to degradation, failure or damage that causes the engine to move away from nominal conditions. The effect that these upsets have on the gas turbine performance range from no effect (i.e., possibly due to a single failed sensor in a multi-sensor system) to a total loss of engine power or thrust control (i.e., for a failed actuator or damaged engine component). The technical steps that are required for engine health management to regain a desired level of performance given a change in performance from nominal include: detection (i.e., determining the presence of a change), isolation (i.e., determining the location or cause of the change), identification (i.e., determining the magnitude of the change), and accommodation (i.e., reconfiguring or adapting the controls to achieve optimal available performance and/or operability). There is great difficulty in performing all of these steps in an optimal fashion for all degraded, failed and/or damaged modes of the gas turbine. For this reason, approaches based on fault and damage adaptation of model-based controls appear well suited for fast detection and identification of engine degradation, faults, failures and damage, as well as for adequate control recognition and reconfiguration in the presence of such upsets, so that engine performance and/or operability can be optimized.
Currently, gas turbine systems rely on sensor-based control systems, in which operating goals and limits are specified and controlled in terms of available sensed parameters. Online engine health management is typically limited to sensor failure detection (i.e., range and rate checks), actuator position feedback errors, and some selected system anomaly checks, such as stall detection, rotor overspeed, and other such indications of loss of power or thrust control. When an engine component or system fails, or if a fault is detected therein, the fault/failure of the component/system is handled on an individual basis (i.e., each component/system is controlled by its own control regulator or heuristic open-loop logic). Additionally, fault accommodation logic in existing control systems only leads to an a priori determined set of possible corrective control actions that can be taken to correct a given fault or failure. Therefore, if the particular fault or failure has not been previously programmed into the set of possible corrective control actions, the control system may not select the optimal solution to correct the fault/failure because the optimal solution may not be present. Damage situations, such as when a rotating engine component is damaged, are not even currently addressed specifically by existing control systems.
There are presently no deterioration, fault, failure and/or damage adaptive model-based control systems and methods available. Thus, there is a need for such control systems and methods. There is also a need for such control systems and methods wherein the models, optimizations, objective functions, constraints and/or parameters in the control system modify, update and/or reconfigure themselves whenever any engine component or system moves away from nominal so that as much performance and/or operability as possible can be regained. There is yet a further need for such systems and methods wherein the control system updates itself in real-time. There is also a need for such systems and methods to be automated using a computer. There is still a further need for such systems and methods to take information about detected deterioration, faults, failures and damage and incorporate such information into the proper models, optimizations, objective functions, constraints and/or parameters in the control system to allow the control system to take optimized action given the current engine condition. There is also a need for such systems and methods to allow any level of deterioration, faults, failures or damage to be accommodated, not just deterioration, faults, failures or damage that have a priori solutions already programmed into the system. Furthermore, there is a need for such systems and methods to be capable of being used to control gas turbines, such as the gas turbines in an aircraft engine, power plant, marine propulsion, or industrial application.
Accordingly, the above-identified shortcomings of existing systems and methods are overcome by embodiments of the present invention, which relates to adaptive model-based control systems and methods. An embodiment of this invention comprises systems and methods wherein the models, optimizations, objective functions, constraints and/or parameters in the control system modify, update and/or reconfigure themselves whenever any engine component or system moves away from nominal so that as much performance and/or operability as possible can be regained. In some embodiments, the models, optimizations, objective functions, constraints and/or parameters in the control system update themselves in real-time, and in some embodiments the systems and methods are automated using a computer. Embodiments of the systems and methods of this invention may take information about detected deterioration, faults, failures and damage and incorporate such information into the models, optimizations, objective functions, constraints and/or parameters in the control system to allow the control system to take optimized action given the current engine condition. Embodiments of the systems and methods of this invention may allow any level of deterioration, faults, failures or damage to be accommodated, not just deterioration, faults, failures or damage that have a priori solutions already programmed into the system. Furthermore, embodiments of the systems and methods of this invention may be capable of being used to control gas turbines, such as the gas turbines in an aircraft engine, power plant, marine propulsion or industrial application.
This invention comprises adaptive model-based control systems and methods wherein the model(s) is adapted to represent the engine that it is controlling. The adaptation of the model(s) allows the control system to make more informed and/or optimal decisions about how to adapt or reconfigure the control when the engine has moved away from nominal conditions. This adaptation includes effects from engine-to-engine variation, deterioration, faults, failures and/or mechanical damage in the engine components themselves, or in any of the engine control systems or components thereof.
These adaptive model-based control systems may detect deterioration, faults, failures and/or damage, and then take such information and incorporate it into the models, optimizations, objective functions, constraints and/or parameters in the control system, preferably in real-time. This information allows the control system to take optimized action given the current engine conditions. Since these control systems are updated and adapted in real-time, they allow for any level of deterioration, faults, failures or damage to be accommodated, not just deterioration, faults, failures and damage that have a priori solutions already programmed into the model(s) in the control system.
These adaptive model-based control systems and methods are designed to reduce operator workload and enable autonomous gas turbine operation by: (1) providing sufficient information to the supervisory control so that the supervisory control can manage propulsion, power and/or electrical output for the given mission or event; (2) elevating the level of autonomy in the engine control; (3) aiding the integration of the engine control with the supervisory control; and/or (4) improving engine-related decision-making capabilities.
Many model-based control systems are created by designing a model of each component and/or system that is to be controlled. For example, there may be a model of each engine component and systemxe2x80x94compressor, turbine, combustor, etc. Each model comprises features or dynamic characteristics about the component""s or system""s behavior over time (i.e., speed accelerations being the integral of the applied torques). From the model(s), the system may control, estimate, correct or identify output data based on the modeled information. For example, if thrust or power is lost because an actuator is stuck in a specific position, the system can hold the control to that actuator fixed as an input constraint, and then adapt the controls that are output to the other actuators so that no other constraints are violated, and as much lost thrust or power as possible can be regained so that the gas turbine may continue operation.
This invention allows either performance or operability to be optimized. If the performance-optimizing mode is selected, the objectives include attempting to maximize or minimize thrust, power, electricity, specific fuel consumption, part life, stress, temperatures, pressures, ratios of pressures, speed, actuator commands, flows, dollars, costs, and the like. This will lead to longer engine run times, fuel savings, increased transient performance, increased parts life, and/or lower costs for operating the engines. If the operability-optimizing mode is selected, the objectives include attempting to manage stall margin, increase operability, and prevent in-flight mishaps. This will lead to a reduction of loss of thrust or loss of power control events, increased engine survivability, and increased engine operating time in the presence of deterioration, faults, failures and/or damage.
This invention comprises adaptive model-based control systems and methods that comprise a system model, estimators, model-based diagnostics, and a model-based control(s) or model-predictive control(s). Physics-based models and empirical models provide analytical redundancy of sensed engine parameters, and access to unmeasured parameters, for control and diagnostics purposes. These models also predict future behavior of the system. Estimators associated with the various models estimate the model state, and ensure that the models are providing accurate representations of the engine and its subsystems and components. Model-based diagnostics provide accurate engine condition information (i.e., deterioration, damage, and engine system faults and/or failures), relying both on models and sensed parameters. Model-predictive control maintains robust, high-performance control of the engine in the presence of component and/or system deterioration, faults, failures and/or damage and mission segment-specific operational goals, using the predictive capabilities of the model and information from the model-based diagnostics. Overall health management of the engine comes from the confluence of on-board diagnostics, a fault-tolerant control, and the adaptation of the model-based controller(s).
Further features, aspects and advantages of the present invention will be more readily apparent to those skilled in the art during the course of the following description, wherein references are made to the accompanying figures which illustrate some preferred forms of the present invention, and wherein like characters of reference designate like parts throughout the drawings.